Computational Physics
A Scoping Review of Physics Informed Machine Learning for Wave Propagation Modeling in Seismology
Óscar Rincón-Cardeño, Gregorio Pérez-Bernal, Silvana Montoya-Noguera et al. (+1 more)
Standard numerical methods accurately simulate seismic waves but are computationally expensive, particularly for inverse problems. Some machine-learning-based alternatives have emerged, promising to reduce cost while preserving physical accuracy. This scoping review, drawing on OpenAlex and Scopus, maps physics-informed machine learning applications to seismic wave propagation based on partial differential equations, classifying selected studies by problem type (forward or inverse) and learning strategy to uncover trends, patterns, and gaps. Results show that these methods have been applied to both forward modeling and inversion, often matching standard numerical accuracy at lower cost. We identified three mechanisms for incorporating physical knowledge into models: observational, inductive, and learning bias. We implemented a PyTorch replication of the original PINN framework to test methodological reproducibility of a representative method, obtaining results consistent with and, in most cases, more accurate than those originally reported. Based on the reviewed literature, we identified limitations in benchmarking consistency, training cost, and scalability to three-dimensional and experimentally validated problems. We conclude that while standard numerical methods remain foundational, physics-informed machine learning serves as a complementary tool valuable for inverse problems and surrogate modeling, with future work needing consistent benchmarking, hybrid formulations, and validation under realistic geophysical conditions. The continued development of these methods, particularly through hybrid formulations and reproducible benchmarking, may broaden their role in seismological workflows, although realizing this potential will need addressing current limitations in scalability.
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All authors Óscar Rincón-Cardeño, Gregorio Pérez-Bernal, Silvana Montoya-Noguera, Nicolás Guarín-Zapata
Chemical Physics
Irreducible Representations as Multireference Indicators for Diradicaloid Systems
Emmalyn A. Sarver and Lukas Muechler
Multireference behavior in molecules often arises when a small gap between frontier orbitals results in mixing of closed and open-shell configurations. Standard multireference diagnostics of this regime usually rely on correlated wavefunctions, natural-orbital occupations, or reduced density
matrices. Here, we examine a complementary,
symmetry-based criterion for a model system. For a time-reversal-invariant
Hamiltonian, a
symmetry-preserving, closed-shell Slater determinant must transform as the trivial irreducible representation of its point group. Therefore, a nontrivial, many-electron irreducible representation excludes such a description. We compare two pathways within the same model to demonstrate this. Along the control pathway, the frontier orbitals remain separated and the ground state retains a trivial irreducible representation over the weak-to-intermediate interaction regime. Along the obstructed pathway, a high-
symmetry point produces a frontier-orbital degeneracy, resulting in a singlet ground state with two-configuration character and a nontrivial irreducible representation. Exact diagonalization, a two-state effective model, and the Frobenius norm of the two-particle cumulant provide a consistent picture in this regime, demonstrating that irreducible representations can serve as a low-cost diagnostic of multireference character in diradicaloid models. While
symmetry is not a quantitative measure of correlation strength, it does offer a computationally inexpensive screening tool to identify obstructions to a single-reference description.
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Optics
Demodulating Digital Holograms with Unknown Uniform Phase-shifts by Spiral Phase Transform
Pavel Trochtchanovitch
The Spiral Phase Transform (SPT) is a generalization of the
Hilbert transform for 2D signals and, as such, can be used for AC signal demodulation. However, phase demodulation with the SPT is complicated by a multiplicative term that depends on the fringe directional map. We derived an analytical formula for the twofold directional map and applied the SPT for the blind reconstruction of phase-shifted digital holograms. Possible phase ambiguities in the unfolded directional map were resolved by satisfying the spatial uniformity condition of the phase shifts. The method was experimentally verified using on-axis and off-axis digital holograms of specularly reflecting subjects.
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Instrumentation and Detectors
Fast and bright scintillators for ultrafast materials dynamics using 4th generation synchrotron
Zhehui Wang, Dana Dattelbaum, Rachel Huber et al. (+13 more)
We present recent advances in fast and bright scintillators for ultrafast X-ray phase contrast imaging of dynamic materials experiments at the upgraded Advanced
Photon Source (APS-U), a fourth generation synchrotron. APS-U enables hard X-ray imaging at frame rates of at least 13 MHz (corresponding to 77 ns or shorter interframe intervals), creating a new need for scintillators with faster response and higher light output than lutetium yttrium oxyorthosilicate (LYSO). For indirect imaging and diffraction with ultrafast cameras, commercial lanthanum bromide (LaBr3) and cerium bromide (CeBr3) are promising candidates. These materials exhibit decay times approximately a factor of two shorter than LYSO (around 40 ns) and lutetium oxyorthosilicate (LSO), while maintaining comparable light yield per incident X-ray
photon. However, their implementation at APS-U requires addressing several challenges, including material limitations due to hygroscopicity, efficient optical coupling to imaging systems, and high
quantum efficiency for conversion of scintillation light, predominantly at wavelengths below 400 nm, into detectable electronic signals. We report results from material characterization, detector integration and packaging, and beamline experiments of materials with impact. In addition, emerging scintillator classes, including perovskites and high-
entropy materials, are discussed as potential alternatives for next-generation ultrafast X-ray diagnostics.
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All authors Zhehui Wang, Dana Dattelbaum, Rachel Huber, Quanxi Jia, Yuelin Li, Katie Liu, C. L. Morris, Brad D. Price, Robert Reinovsky, Adam Schuman, Nicholas Sinclair, Maria Spiropulu, Yoshimasa Toyoda, Christina Wang, Li-Yuan Zhang, Ren-Yuan Zhu
Chemical Physics
A differential derivation of the Obara-Saika relation for Gaussian electron repulsion integrals
Charles C. Forgy and David A. Mazziotti
The Obara-Saika (OS) method is one of the most widely used techniques in
quantum chemistry for evaluating electron repulsion integrals (ERIs) via a set of recurrence relations that build higher angular momentum integrals from lower-order ones. The original derivation by Obara and Saika proceeded by directly relating integrals of differing angular momentum. In this work, we present a compact novel derivation of the OS vertical recurrence relation based solely on differential relations between Gaussian basis functions, expanding on a method suggested in earlier work. By explicitly deriving the required derivative expressions we identify all non-zero primitive terms contributing to the full ERI to develop a hierarchical formulation of the OS recursion relations. This approach has pedagogical value as a rigorous and self-contained derivation. Additionally, the resulting organization exposes independent primitive derivative quantities and may be useful for code generation and parallel implementations on modern GPU architectures.
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Plasma Physics · Cross-listed from astro-ph.CO
Magneto-Thermal Instability in Galaxy Clusters – III. The Limit of Adiabatic Stratification
Lorenzo Maria Perrone and Henrik Latter
In the hot and dilute intracluster medium of
galaxy clusters, large-scale buoyancy instabilities can develop due to the transport of heat along
magnetic field lines. In particular, the peripheries of
galaxy clusters are unstable to the magneto-thermal instability (MTI), which may contribute to the observed levels of
turbulence. Recent theoretical and numerical work has revealed that the stable background
entropy stratification controls the nonlinear saturation of the instability, by setting the strength and the integral scale of the resulting turbulent state. However, observations of the periphery of
galaxy clusters show that the radial
entropy profiles near the virial radii $R_{500}$ may be flatter than predicted by models of smooth gravitational
accretion. This motivates us to investigate the saturation of the MTI in adiabatic (buoyantly neutral) atmospheres, using both phenomenological approaches and Boussinesq numerical simulations, carried out with the pseudospectral code SNOOPY. We find that the adiabatic MTI saturates in a state characterised by the formation of large-scale plumes and their destruction by shear instability, yielding a new scaling law for the saturated turbulent kinetic energy, $\sim$$\chi \omega_T$, as the adiabatic limit is approached, where $\chi$ is the effective thermal diffusivity and $\omega_T$ is the MTI frequency. This predicts that the MTI plumes may achieve near sonic speeds in cluster outskirts, thus providing significant turbulent pressure support, even in the face of suppressed thermal conduction.
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Instrumentation and Detectors · Cross-listed from hep-ph
Simulation of Axion-Induced Electromagnetic Signal Detection Using Plasmonic Metasurfaces and Diamond NV Centers
James L. Webb
The
axion represents a strong candidate for weakly interacting dark matter. To date, high sensitivity lab based experiments and astrophysical observations have ruled out a substantial part of the
axion mass and
photon coupling parameter space. However, a challenge remains in searching for the presence of the
axion in the higher mass range 0.01-1eV corresponding approximately to
axion field oscillation at THz frequencies. This work investigates via numerical simulation the feasibility of a high sensitivity, lab-based
axion sensor operating in this range, based on plasmonic electric field enhancement by a nanostructured metasurface, combined with heterodyne detection and
quantum sensing via nitrogen-vacancy (NV) centers in diamond. Estimates of the sensor response to anomalous electromagnetic fields resulting from
axion coupling are given using Ti/Au nanopillars on LiNb at
axion mass corresponding to telecommunications wavelength ($\approx$0.8eV, 196 THz). Finally, the possibility of sensing in the lower
axion mass $<$10$^{-2}$ to 10$^{-1}$eV range is explored using alternative materials, with CdTe as an example.
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Fluid Dynamics
Flexibility as a Universal Nature-Inspired Mechanism for Thrust Enhancement
Roberta Santoriello, Francesco Viola and Vincenzo Citro
Nature has equipped jet-propelled swimmers with flexible nozzles that outperform rigid ones, yet the origin of this advantage has remained unexplained. By tracking where and when energy is exchanged between fluid and structure, three-dimensional numerical simulations resolve the underlying mechanism: a standing-wave response of the nozzle, in which the structure dilates and then
recoils synchronously, charging and releasing energy to enhance thrust. Outside of this regime, the structure exhibits a traveling wave response, with expansion and contraction coexisting along the nozzle, reducing the thrust gain. We propose a physics-based model that captures the boundary between standing and traveling responses in a closed form, showing that the optimum occurs when the natural period of the structure matches the pulse duration. Beyond this optimum the strain imposed by the nozzle
curvature required for steering selects the geometry observed across marine species. The propulsion and maneuverability are reconciled within a single framework that yields design principles for soft robotic propulsors.
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Atomic Physics
Cesium Based Laser-Atomic Oscillator
Saurabh Pandey, Roger Ding, George Burns et al. (+1 more)
We report the first demonstration of a
laser-atomic oscillator with cesium (Cs) atoms. A
laser-atomic oscillator (LAO) is analogous to an active mode-locked
laser with a self-excited modulator, i.e. atoms, at a ground-state hyperfine transition frequency. Therefore, a LAO can be configured as the simplest active atomic clock or a self-oscillating, earth-field atomic magnetometer that delivers oscillation signals both optically and electrically. With the current experimental Cs-LAO setup, when it is configured as an atomic clock using the 0–0 hyperfine transition, the short-term fractional frequency instability is around 10$^{-10}$ level. When it is configured as a self-oscillating magnetometer using a magnetically-sensitive hyperfine transition, the
magnetic field sensitivity is around 100 fT/$\sqrt{\rm{Hz}}$ at 60 Hz. The presented Cs-LAO uses a cavity length from $\sim6.5$ cm to $\sim11.4$ cm. Ultimately, the minimal length of a Cs-LAO device can be $\leq1.63$ cm. Our new efforts unlock the potential of building truly chip-scale atomic clocks and magnetometers.
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All authors Saurabh Pandey, Roger Ding, George Burns, Yuan-Yu Jau
Biological Physics · Cross-listed from cond-mat.stat-mech
Multifractal Scaling in Hi-C Maps
Seong-Gyu Yang, Lucas Hedström, Jan Smrek et al. (+1 more)
The three-dimensional organization of the genome exhibits rich, scale-dependent structure, as revealed by both chromosome contact maps (e.g., Hi-C maps) and chromatin density measured by microscopy. Recent studies have reported multifractal scaling in these data. Yet, the origin of this scaling behavior remains unclear: existing efforts describe it through postulated models. Here, we show that the multifractal structure of Hi-C maps is a direct consequence of the power-law contact probability $P(s)$, which is itself an empirical observable measured from Hi-C maps. Starting from $P(s)$ with a single exponent $\gamma$, we analytically derive the mass exponent $\tau(q)$, which characterizes how the $q$-th moment of contact density scales with box size $l$ used to coarse-grain the genomic coordinate. This multifractal behavior reflects the
geometric competition between intra- and inter-segment contacts. We find that the slope of $\tau(q)$ at large $q$ is given by $2 -\gamma$ when $\gamma <1$, and by $1$ when $\gamma \geq 1$. We further show that this behavior is robust to noise and consistent across diverse organisms, indicating that it is a universal feature of chromatin organization. We extend our analysis into double-exponent $P(s)$, and show the $l$ dependence in multifractal behavior. Taken together, these results provide a physical explanation for multifractal scaling and establish a direct link between the multifractality in Hi-C maps and
polymer contact statistics, with the large-$q$ slope of $\tau(q)$ mapping onto a known
polymer contact exponent.
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All authors Seong-Gyu Yang, Lucas Hedström, Jan Smrek, Ludvig Lizana
Computational Physics · Cross-listed from math.NA
GQL-Based Physical-Constraint-Preserving High-Order Finite Difference Schemes for Special Relativistic Hydrodynamics in Arbitrary Dimensions
Linfeng Xu, Shengrong Ding and Kailiang Wu
High-order accurate simulations of special relativistic hydrodynamics (RHD) are prone to numerical breakdown if intrinsic physical constraints (positive rest-mass density/pressure and subluminal velocity) are violated near strong discontinuities. In this work, we develop a robust and efficient physical-constraint-preserving (PCP) flux-limiting framework for high-order schemes, using finite-difference WENO as a representative example. By leveraging the
geometric quasilinearization (GQL) representation, which equivalently reformulates the nonlinear RHD constraints into a family of linear inequalities, we integrate a Zalesak-type Flux-Corrected Transport (FCT) update into a scalar-style limiter that acts directly on conservative variables. A critical innovation is the explicit, non-iterative determination of limiting parameters via a rational stereographic parameterization of the GQL normal vector. This technique transforms the required worst-case minimization over auxiliary variables into a generalized Rayleigh-quotient formulation, allowing the optimal parameters to be obtained by solving small symmetric
eigenvalue problems ($2\times2$ in 1D; $(d+1)\times(d+1)$ in $d$ dimensions). Relaxed variants are further introduced to reduce computational costs in multidimensions while retaining the PCP guarantee. Extensive numerical
benchmarks ranging from 1D to 3D, including ultra-relativistic Riemann problems and astrophysical jets, demonstrate that the proposed method robustly enforces physical admissibility, sharply resolves discontinuities, and maintains design-order accuracy for smooth solutions.
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Optics · Cross-listed from nlin.PS
Dissipative surface solitons in two-dimensional truncated lattices with linear gain and loss
Changming Huang, Yan Wang, Pengcheng Liu et al. (+2 more)
Dissipative
solitons constitute a robust class of self-localized nonlinear states sustained by the dynamic balance between nonlinearity and gain-loss, possessing an intrinsic stability that stems from their fundamental attractor nature. When combined with
lattice truncation, this balance gives rise to dissipative surface
solitons (DSSs), whose existence and stability are jointly dictated by boundary-induced confinement and non-Hermitian dynamics. In two-dimensional truncated
lattices with linear gain and loss, surface localization emerges within gap regimes, where families of DSSs bifurcate from linear surface localized gain modes as the nonlinearity increases. Increasing the number of waveguide rows at the interface enriches the diversity of supported surface modes in both linear and nonlinear regimes. Although multiple DSS families with distinct phase configurations may coexist within the same gap, their dynamical stability is strongly phase selective. These insights establish linear gain-loss engineering as a powerful mechanism for controlling nonlinear surface localization and provide practical guidelines for realizing robust nonlinear surface states in gain-loss-tailored photonic platforms.
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All authors Changming Huang, Yan Wang, Pengcheng Liu, Qidong Fu, Liangwei Dong
Atmospheric and Oceanic Physics · Cross-listed from stat.AP
Locally stationary Argo ocean heat content estimates: Modeling, validation and uncertainty quantification
Thea Sukianto, Mikael Kuusela, Donata Giglio et al. (+3 more)
Argo profiling floats measure seawater temperature and salinity in the upper 2000 meters of the ocean. These floats are uniquely capable of measuring the global Ocean Heat Content (OHC), a quantity that is of central importance for understanding Earth Energy Imbalance. Yet, producing Argo-based OHC estimates with reliable uncertainties is statistically challenging due to the complex structure and large size of the Argo
dataset. Here we present an end-to-end mapping and uncertainty quantification framework for Argo-based OHC estimation using state-of-the-art methods from spatio-temporal statistics. The framework is based on modeling vertically integrated Argo temperature profiles as a locally stationary Gaussian process defined over space and time. This enables us to produce computationally tractable OHC anomaly maps based on data-driven decorrelation scales estimated from the Argo observations. Our modeling choices are validated using statistical cross-validation, which demonstrates the importance of including a climatological time trend in the mean field and accounting for time in the covariance function. We quantify the uncertainty of these maps using local conditional simulation ensembles, a novel approach that leads to principled spatially and temporally correlated uncertainty quantification. A new paired cross-validation technique is presented to validate these uncertainties. The mapping framework is implemented in an open-source codebase that is designed to be modular, reproducible and extensible. To demonstrate the mapping and uncertainty quantification capabilities of this approach, we present new Argo OHC maps with uncertainties for 2004-2022 and report on various downstream climatological estimates and their uncertainties.
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All authors Thea Sukianto, Mikael Kuusela, Donata Giglio, Anirban Mondal, Pulong Ma, Douglas W. Nychka
Chemical Physics
Resonant and collective modification of London dispersion interactions under vibrational strong coupling
Marit R. Fiechter and Jeremy O. Richardson
Experiments have shown that, by tuning a microcavity to resonance with a vibrational mode of the molecules contained within it, one can modify chemical properties, such as reaction rates. This gives rise to the exciting prospect of steering chemical reactivity, just by placing a pair of carefully spaced mirrors around the reaction mixture. However, a decade after the first demonstration, the mechanism behind this effect remains ill-understood. Here, we show how vibrational strong coupling can lead to resonant modification of vibrationally-resolved London dispersion interactions. Employing a mixed
quantum-classical dynamics scheme, we then show how this in turn can give rise to resonant rate enhancement in the case of two molecules strongly coupled to the cavity mode, for all regimes of solvent friction. The resonant changes of the London dispersion interaction seem to persist when increasing the number of molecules. Whether this also leads to altered reaction rates in the experimentally relevant collective limit remains an open question, as this regime falls outside the range of applicability of our mixed
quantum-classical dynamics approach. Nevertheless, the framework presented here offers an exciting new avenue to explore, and hopefully bring us a step closer towards explaining the mechanism behind vibropolaritonic chemistry.
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Computational Physics
Conditional Normalizing Flow for Gas-Surface Scattering from Thermal to Hypersonic Velocities
Miklas Schütte, Stephen Hocker, Hansjörg Lipp et al. (+3 more)
Accurate aerodynamic modeling of satellites in very low Earth orbit (VLEO) requires gas-surface interaction (GSI) models that capture the full velocity spectrum from thermal to orbital speeds. Atmospheric particles initially strike spacecraft surfaces at hypersonic velocities of 6 000 - 10 000 m/s. Due to surface roughness and complex geometries, especially within air-breathing electric propulsion (ABEP) intake systems, multiple collisions occur, progressively reducing the particle velocities. A recent machine learning framework for deriving scattering kernels from molecular dynamics (MD) simulations has shown promise, but remains limited to high-velocity single impacts and possibly violates fundamental
equilibrium principles such as detailed balance. This work extends this machine learning based scattering kernel to cover the complete velocity range using conditional normalizing flows trained with physics-informed constraints, enabling accurate modeling of multi-bounce scenarios in realistic VLEO applications. We train a conditional Real-valued Non-Volume Preserving (cRealNVP) model on expanded molecular dynamics simulations covering velocities from thermal to hypersonic speeds, incorporating a detailed balance loss term. The resulting model demonstrates improved accuracy compared to previous approaches even in the original high-velocity regime, while successfully capturing thermal-velocity scattering. Quantitative assessment shows that thermalization is approximated within acceptable tolerances. This framework provides essential capabilities for accurate ABEP intake optimization and VLEO mission planning while offering a general methodology applicable to broader rarefied gas dynamics problems requiring thermodynamic consistency.
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All authors Miklas Schütte, Stephen Hocker, Hansjörg Lipp, Johannes Roth, Stefanos Fasoulas, Marcel Pfeiffer
Chemical Physics
Conical Intersections Enable Ultrafast Molecular Spin Control in a Chromium Complex
Zihui Liu, Junhua Zhou, Tianrui Chen et al. (+8 more)
Molecular spintronics seeks to control
spin states in single molecules for ultrafast switching and efficient information processing. Transition metal complexes are promising candidates for such applications due to their modular ligand fields, diverse
spin configurations, and potential for
spin-vibronic coupling that facilitates rapid
spin dynamics. Chromium(III) complexes, in particular, offer long-lived emissive doublet states and chemical robustness, making them attractive for room-temperature
spin control. Here we investigate the
spin-state dynamics of tris(2,4-pentanedionato)chromium(III), [Cr(acac)3], a photochemically stable d3 complex with minimal vibrational congestion. Using ultrafast transient grating and two dimensional electronic spectroscopy with ~10 fs resolution, we directly probe vibrational and electronic dynamics associated with the 4T2 -> 2E intersystem crossing (ISC). These measurements reveal coherent vibrational modes implicated in mediating nonadiabatic
spin transitions. Complementary theoretical modelling shows that vibronic coupling and
spin orbit interactions promote the formation of multiple conical intersections, providing ultrafast channels for
spin-flip dynamics. Metal-ligand bending and stretching modes serve as tuning and coupling coordinates, enabling ISC despite weak
spin-orbit coupling in 3d transition metal. Our study provides mechanistic insight into
spin-vibronic dynamics in Cr(III) complexes and establishes a design framework for achieving ultrafast molecular
spin switching, advancing the development of optically addressable
spin centres for future spintronic and
quantum technologies.
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All authors Zihui Liu, Junhua Zhou, Tianrui Chen, Michael Penny, Sara Mosca, Mengyuan Cui, Vandana Tiwari, R. J. Dwayne Miller, Fulu Zheng, Ajay Jha, Hong-Guang Duan
Atomic Physics · Cross-listed from quant-ph
State-dependent Gaussian gate set using an optical tweezer for trapped ions
Philip Leindecker, Luka Milanovic, Tanja Behrle et al. (+5 more)
We demonstrate a state-dependent Gaussian gate set on the motional modes of trapped $^{40}$Ca$^+$ ions, realized with an optical tweezer. Dynamic control of the tweezer intensity and position enables local displacement, squeezing, phase-space rotation, and beamsplitter operations, constituting a complete gate set. By varying the tweezer position relative to the ion, we show how the strength of each operation is set by the corresponding spatial derivative of the local optical potential. We further demonstrate the inherent dependence of each operation on the ion's internal state and use coherent
spin-motion coupling provided by the tweezer to create a motional cat state. Our work establishes optical tweezers as a unified and local resource for continuous-variable
quantum control in trapped ion systems.
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All authors Philip Leindecker, Luka Milanovic, Tanja Behrle, Edgar Brucke, Matteo Marinelli, Julian Schmidt, Jonathan Home, Cornelius Hempel
Chemical Physics · Cross-listed from cond-mat.soft
Optimal interactions for addressable self-assembly
Tighe McAsey, Sushrut Tadwalkar, Ali Fele-Paranj et al. (+1 more)
Addressable self-assembly asks that each building block assemble into a particular location in a target structure. Although particles may all be distinct, achieving high yield is a challenge because of monomer depletion: more target structures can nucleate than there are building blocks for, so they form partial fragments which cannot complete growth. We ask how to design the interactions between building blocks to achieve the highest yield in a given time. Using reaction equations describing all the intermediate steps of assembly, combined with numerical optimization, we show that the optimal interactions are such that (i) all bonds are either very strong or very weak, and (ii) the strong bonds form a spanning tree of the target structure. We then prove that when interactions form a spanning tree, monomer depletion cannot occur: assembly can always proceed downhill in energy space, with no kinetic traps. This result is a combinatorial property of the underlying interaction graph, and does not depend on the particular model for the kinetics. It suggests a robust design principle: create a network of strong interactions that has no loops, and make all other interactions much weaker. We validate this principle in numerical simulations of larger structures, and we further show that spanning trees that are more compact have typically better yield. Our results suggest a new framework for understanding monomer depletion and addressable self-assembly, which may be applied to DNA nanotechnology and which may give insight into the assembly pathways of certain multiprotein complexes.
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All authors Tighe McAsey, Sushrut Tadwalkar, Ali Fele-Paranj, Miranda Holmes-Cerfon
Computational Physics
Navigating committor landscape of biomolecules with a general pairwise interaction model
Jintu Zhang, Zichang Jin, Huifeng Zhao et al. (+5 more)
Sampling rare conformation transitions between metastable states is a central challenge in atomistic simulations. While the committor function serve as an ideal reaction coordinate for driving enhanced sampling, their high-dimensional inputs and complex functional forms limit the efficacy of standard feedforward neural networks in modeling them. Inspired by recent breakthroughs in biomolecular structure prediction, we propose a novel committor learning framework grounded in the AlphaFold 3 paradigm. By integrating a lightweight, differentiable atom-level
embedding with a simplified Pairformer architecture, our method inherently captures intricate dynamical features of diverse biosystems without requiring specialized prior knowledge. We demonstrate the superior expressiveness and accuracy of the proposed framework across multiple atomistic processes. For the folding of the chignolin mini-
protein, our model reveals the finer-grained structure of its transition state ensemble (TSE) and a detailed bifurcated reaction mechanism. Furthermore, for calixarene host-guest systems, we develop a unified committor model that elucidates how ligand substituents regulate the ratio between distinct binding pathways, offering new perspectives for structure-based drug design.
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All authors Jintu Zhang, Zichang Jin, Huifeng Zhao, Kai Zhu, Bowei Zhao, Xujun Zhang, Peilin Kang, Tingjun Hou
Instrumentation and Detectors · Cross-listed from astro-ph.IM
The On-Sky Performance of the LSST Camera CCD Array
Sean Patrick MacBride, Aaron Roodman, Stuart Marshall et al. (+88 more)
The focal plane of the LSST Camera contains 189 individual science CCDs, arranged into 21 raft tower modules, along with 4 wavefront and 8 guider CCDs located in 4 additional corner RTMs. Altogether, the LSST Camera CCDs compose the largest focal plane ever constructed. The LSST Camera is the primary instrument of Rubin Observatory, which will begin the Legacy Survey of Space and Time in 2026. In this paper, we describe the on-sky performance of the LSST Camera CCDs, from receipt at NSF/DOE Vera C. Rubin Observatory in May 2024 to on-sky observations during the first year of operations. We discuss the process to establish functionality of several CCDs which were affected by an electrical short and faulty analog-digital converter, optimizations of readout timing in response to changes in the survey strategy, and implementation of enhanced focal plane safety measures through an active clearing mechanism on the CCDs. Finally, we discuss sensor features observed on-sky, and global performance during the first year of operations. The operations to date of the LSST Camera CCDs have demonstrated the capability of performing a wide, fast, and deep optical imaging survey of the entire southern sky at the Rubin Observatory.
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All authors Sean Patrick MacBride, Aaron Roodman, Stuart Marshall, Yousuke Utsumi, Kevin Fanning, John Banovetz, Theo Schutt, Alexander Broughton, Shuang Liang, Andrew P. Rasmussen, Pierre Antilogus, John Gregg Thayer, Homer Neal, Anthony S. Johnson, Pierre Astier, Seth W. Digel, Andrew Bradshaw, Johan Bregeon, James Chiang, Céline Combet, Guillaume Dargaud, Johnny H. Esteves, Marcelle Soares-Santos, Thibault Guillemin, Claire Juramy-Gilles, Craig S. Lage, Myriam Migliore, Daniel Polin, J. Anthony Tyson, Renee Nichols, Steven M. Ritz, Eli S. Rykoff, Adrian Shestakov, Adam Snyder, Max Turri, Duncan Wood, Travis Lange, Martin Nordby, Hannah Mary Margaret Pollek, Shawn Osier, Boyd Bowdish, Diane Hascall, Margaux Lopez, Scott P. Newbry, Juan Carlos Lazarte, Vincent Lee, Michael Silva, Dave Kiehl, Andrew Hau, Tom Nieland, Nico Linton, David Shelley, Yongqiang Qiu, Mark Freytag, Stephen Cisneros, Chris Mendez, Stephen A. Tether, Alan M. Eisner, Dmitry Onoprienko, Owen Saxton, Kevin A. Reil, Vincent J. Riot, Justin Wolfe, Scott E. Winters, Brian J. Bauman, William Wahl, Paul O'Connor, Françoise Virieux, Alexandre Boucaud, Camille Parisel, Éric Aubourg, Eric Lagorio, Pierre Karst, Aurélien Marini, Didier Laporte, Francis Vezzu, Guillaume Daubard, Patrick Breugnon, Tim W. Bond, Eric Charles, Richard Dubois, Steven M. Kahn, Andrés A. Plazas Malagón, Rafe H. Schindler, Joanne Bogart, Hye Yun Park, Aurélien Barrau, Christopher Z. Waters, Merlin Fisher-Levine, Antoine Bernard, Mile Kusulja
Physics and Society
Feedback dynamics in matching networks drive behavioral differentiation despite overlapping objectives
Alexandros Gelastopoulos
Many bipartite social networks exhibit pronounced asymmetries in selectivity and matching opportunities: members of one side can afford to be highly selective, while members of the opposite side are forced to accept less desirable matches. While it is natural to try to explain this asymmetry in terms of the intrinsic characteristics of the two sides or other exogenous factors, here we show that such asymmetries can also emerge endogenously through a feedback process generated by the matching process itself: as one side becomes more selective, the other side is pushed to be less selective due to reduced matching opportunities, and vice versa. We develop a model in which individuals repeatedly form one-to-one matches across two groups and adapt their selectivity to achieve a target matching rate. Using both analytic and numerical methods, we show that when encounters are sufficiently frequent, the unique
equilibrium is for one group to be highly selective and the other non-selective. This qualitative outcome holds even for heterogeneous groups with overlapping, almost indistinguishable distributions of target matching rates. The model makes several testable predictions, and it provides a mechanism for behavioral differentiation in repeated matching environments, with applications ranging from online dating to hiring and housing
markets.
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Chemical Physics · Cross-listed from quant-ph
Correlation is magic in electronic structure Hamiltonians
Basie Seibert, Sam Alterman, Qingfeng Wang et al. (+3 more)
The gate and
qubit requirements of
quantum computations of electronic structure have been extensively studied. However, the
quantum resources present in electronic ground states, as measured by
entanglement and magic, remain less well understood. We study the relationship between correlation in electronic structure
Hamiltonians and magic as measured by the 2-stabilizer Renyi
entropy (2-SRE). Perturbative calculations show that the 2-SRE of a given state is proportional to its overlap with a reference stabilizer state. In the context of
quantum chemistry, this links the magic of electronic structure ground states to their Hartree-Fock weight, an established measure of electronic correlation. We then show that the 2-SRE of post-Hartree-Fock ground states is proportional to the correlation energy they recover. We explore this connection through the contextual subspace (CS) method. We present a theoretical framework showing that the CS method can be used to monotonically vary the magic of approximate CS ground states, and we prove that the correlation energy recovered by the CS ground states is proportional to the magic present in the approximate ground state. We present simulation results using 190 molecular species under Jordan-Wigner encoding at a range of bond lengths. The linear relationships between magic and correlation are robust across the
Hamiltonians in our
dataset, but break down at bond lengths beyond the Coulson-Fischer point, where Hartree-Fock fails to capture key physical features of the true ground state wavefunction. By establishing linear relationships for both correlation energy and Hartree-Fock reference weight with the 2-SRE, we conclude that for weakly- and moderately-correlated electronic structure
Hamiltonians, the correlation is directly represented by 2-SRE, and thus by the magic.
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All authors Basie Seibert, Sam Alterman, Qingfeng Wang, Feng Qian, Akimasa Miyake, Peter J. Love
Plasma Physics
Plasma double layer development during high power EUV exposure
Manis Chaudhuri, Pavel Krainov, Dmitry Astakhov et al. (+2 more)
The development of electrostatic
plasma double layer (DL) at the boundary of Extreme Ultra Violet (EUV) exposed and un-exposed region in the bulk volume has been confirmed by 3DPIC (Particle-In-
Cell) simulations in the context of fast transient high power EUV exposures. It is found that the DL exists only for short time scale during EUV-ON time period (~ 70ns) and disappears soon after EUV is OFF. Such DL fingerprint appears above a certain critical value of EUV beam energy (~ 0.1mJ) and it transforms from weak-to-strong DL with further increase of EUV power.
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All authors Manis Chaudhuri, Pavel Krainov, Dmitry Astakhov, Andrei M. Yakunin, Mark van de Kerkhof
Biological Physics · Cross-listed from cond-mat.soft
Nonlinear diffusion and compressive rims in source-driven biopolymer condensates
Avraham Moriel and Howard A. Stone
Many subcellular condensates continuously produce biopolymers. Coupling Flory-Huggins thermodynamics to two-fluid viscoelasticity, we probe the
diffusion of such source-driven polymeric droplets, and identify a universal structural compressive rim at their
diffusion front. Integrating analytical scaling laws, numerical simulations, and experimental data, we show that this framework captures key structural and dynamic characteristics of the nucleolus, demonstrating the role of
polymer diffusion in non-
equilibrium biological transport.
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Physics and Society
Information-Epidemic Dynamics in Cyber-Physical Systems: A Hypergraph Framework with Interpersonal Relationships
Shanchao Peng, Minyu Feng, Liang-Jian Deng et al. (+2 more)
Understanding how information propagation affects epidemic dynamics has become an emerging topic of interest. However, the influence of interpersonal relationship heterogeneity on information acquisition and disease transmission has been largely overlooked. In this work, we introduce a hypergraph structure for Cyber-Physical Systems (CPSs) with two distinct layers. The upper layer, referred to as the cyber layer, consists of a mixed hypergraph, capturing both pairwise propagation and higher-order
diffusion of epidemic-related information. The lower layer, referred to as the physical layer, employs a Susceptible-Infected-Susceptible (SIS) process to capture epidemic spreading. This work introduces an adaptive perception-protection mechanism based on Jaccard similarity, which accounts for interpersonal heterogeneity. In this mechanism, individuals receive information based on their relationships with neighbors and take protective measures accordingly. We analyze the impact of interpersonal relationships and the adoption of neighborhood-based self-protection strategies on epidemic dynamics. Furthermore, we conduct a theoretical analysis based on the Microscopic Markov Chain Approach (MMCA), analytically derive the outbreak threshold, and confirm the results with extensive Monte Carlo (MC) simulations. The results show that stronger interpersonal relationships can promote information propagation, significantly increase the threshold for epidemic outbreaks, and effectively suppress the scale of the epidemic. The study provides theoretical support for designing epidemic control strategies considering interpersonal heterogeneity and improves the understanding of epidemic spreading on hypergraphs.
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All authors Shanchao Peng, Minyu Feng, Liang-Jian Deng, Matjaž Perc, Jürgen Kurths
Optics
Plasmon-Enabled High-Precision Single Molecule Localization Microscopy over an Extended Field of View
Muzzamal I. Shaukat, Carlos E. Rodriguez, M. Suhail Zubairy et al. (+1 more)
We propose PIFLUX, a single-molecule localization scheme combining deep-subwavelength plasmonic illumination with widefield detection. Interference between counter-propagating gap plasmons and a normally incident optical field generates an illumination pattern whose position can be tuned through the plasmon phase while preserving its spatial period. A Cramér-Rao analysis shows PIFLUX reaches few-nanometer precision matching MINFLUX while doubling that of SIMFLUX over a micrometer field of view, and a maximum-likelihood
estimator confirms this on a synthetic
nuclear pore complex.
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All authors Muzzamal I. Shaukat, Carlos E. Rodriguez, M. Suhail Zubairy, Oumeng Zhang
Chemical Physics
Visualizing the Hidden Architecture of Molecular Films with Phase-Resolved Rotational SFG Microscopy
Ben John, Tuhin Khan, Nasim Mirzajani et al. (+3 more)
The highly variable physico-chemical properties of thin molecular films play an essential role in numerous research fields ranging from biophysics to the fabrication of functional devices such as molecular sensors. The properties of molecular films are largely governed by their three-dimensional molecular structure which often exhibits important spatial heterogeneity, either naturally, or introduced deliberately. In order to understand and control these properties microscopic insight into structural parameters such as composition, molecular orientation and conformation, as well as molecular order is required, which, so far, represents a mostly unachieved experimental target. In this contribution we present a powerful experimental approach that can overcome this limitation. Using phase-resolved rotational sum-frequency generation (SFG) microscopy all of these structural parameters can be obtained with sub-monolayer sensitivity and at sub-micron resolution. In measurements of monolayer assemblies of mixed phospholipids, we uncover the molecular packing structure in previously-unattained detail and demonstrate the large potential of the technique for the elucidation of the complex architecture inside molecular films. The structural insight provided by this nonlinear microscopy approach spans all the way from the molecular to the macroscopic scale opening the door to a completely new type of interfacial studies.
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All authors Ben John, Tuhin Khan, Nasim Mirzajani, Martin Wolf, Alexander P. Fellows, Martin Thämer
Fluid Dynamics
Mean-Flow Adjoint Sensitivity Analysis of Unsteady Flow Around Porous Cylinders Using a Homogenized Lattice Boltzmann Method
Shota Ito, Johannes L. Grafen, Fedor Bukreev et al. (+2 more)
Adjoint-based sensitivity analysis is an indispensable tool for large-scale fluid-dynamic design and distributed control problems, yet its application to unsteady and turbulent flows is frequently hindered by the prohibitive
memory footprint of transient checkpointing and the divergence of gradients in chaotic regimes. To address these computational bottlenecks, this paper presents a mean-flow adjoint sensitivity analysis framework for unsteady flows around porous cylinders using the homogenized
lattice Boltzmann method (HLBM). Within this framework, solid structures are efficiently modeled as local porous media utilizing a Brinkman penalization approach. We systematically investigate HLBM-based adjoint gradients for drag and energy dissipation objective functionals, transitioning from steady laminar to unsteady, and finally to turbulent flow regimes. For the turbulent case at Re = 3900, a proof-of-concept is conducted where the framework relies on automatic differentiation to automatically generate adjoint kernels containing subgrid-scale (SGS)
turbulence models for large eddy simulations (LES), circumventing manual derivation and allowing for a direct comparison against the frozen
turbulence assumption (FTA).
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All authors Shota Ito, Johannes L. Grafen, Fedor Bukreev, Adrian Kummerländer, Mathias J. Krause
Physics Education
Notes from the Physics Teaching Lab: Rubidium Atomic Spectroscopy
Kenneth G. Libbrecht
We describe a series of rubidium spectroscopy experiments that can be done using the Teachspin Diode
Laser Spectroscopy instrument, which is commercially available and is already being used in physics teaching labs at over 150 universities. Our goal here is to provide a detailed examination of the capabilities of this instrument, including numerous examples of measurements and data analysis, presented as a supplement to the Teachspin users manual. Our hope is that instructors using this product or similar diode-
laser-based Rb spectroscopy systems will find the experiments described here useful for designing and implementing the curricula in their own physics teaching labs.
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Chemical Physics
Contrastive Regularization of Machine Learning Potentials
Dimitrios Tzivrailis, Georgios Sotiropoulos, Alberto Rosso et al. (+1 more)
Machine learning models are increasingly trained as regressors and then deployed as generators, from
language models to learned simulators. In this setting, accuracy on held-out data says little about the distribution a model produces when it is sampled. We study this problem where the correct distribution is fixed by first principles, in machine learning interatomic potentials (MLIPs) trained by minimizing the mean squared error (MSE) on density functional theory (DFT) energies and forces, then used to run molecular simulations. The MSE never constrains the Boltzmann distribution that the potential defines, so an MLIP can match held-out DFT data and still drift, when sampled, into spurious minima that corrupt its thermodynamics. Building on the variational principle of statistical physics, we introduce Contrastive Regularized MSE (CRMSE), a post-training step in which the potential acts as its own energy-based model and learns to reproduce the distribution it generates, without any new DFT data. On molecules from the MD17
benchmark, CRMSE restores physical sampling and recovers DFT free-energy profiles, while keeping energy and force errors within chemical accuracy. Our results suggest that a model meant to be sampled must be trained on the distribution it produces, not only for pointwise accuracy.
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All authors Dimitrios Tzivrailis, Georgios Sotiropoulos, Alberto Rosso, Eiji Kawasaki